Transforming Nanomedicines From Lab Scale Production to Novel

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Transforming Nanomedicines From Lab Scale Production to Novel Clinical Modality Dalit Landesman-Milo, and Dan Peer Bioconjugate Chem., Just Accepted Manuscript • DOI: 10.1021/acs.bioconjchem.5b00607 • Publication Date (Web): 06 Jan 2016 Downloaded from http://pubs.acs.org on January 12, 2016

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Bioconjugate Chemistry

Transforming Nanomedicines From Lab Scale Production to Novel Clinical Modality Dalit Landesman-Milo1,2,3 and Dan Peer1,2,3 * 1.

Laboratory of NanoMedicine, Department of Cell Research and Immunology,

George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel; 2.

Department of Materials Science and Engineering, The Iby and Aladar Fleischman

Faculty of Engineering. 3. Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv 69978, Israel * To whom correspondence should be addressed. D.P. Tel: +972-3-6407925; Fax: +972-3-6405926; Email: [email protected]

Keywords: Nanomedicine, cancer biology, preclinical animal models, combination therapy.

Abstract The use of nanoparticles as anti-cancer drug carriers has been studied for over 50 years. These nanoparticles that can carry drugs are now termed “nanomedicines”. Since the approval of the first FDA ‘nanodrug’, DOXIL® in 1995, tremendous efforts have been made to develop hundreds of nanomedicines based on different materials. The development of drug nanocarriers (NCs) for cancer therapy is especially challenging and requires multidisciplinary approach. Not only the translation from a lab scale production of the NCs to clinical scale is a challenge, but also tumor biology and its unique physiology possess challenges that need to be overcome with cleverer approaches. Yet, with all the efforts made to develop new strategies to deliver drugs (including small molecules and biologics) for cancer therapy, the number of new NCs that are reaching clinical trials is extremely low. Here we discuss the reasons why most of the NCs loaded with anti-cancer drugs are not likely to reach the clinic and emphasize the importance of understanding tumor physiology and heterogeneity, the use of predictive animal models and the importance of sharing data as key denominators for potential successful translation of NCs from a bench scale into clinical modality for cancer care.

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Introduction The Balance between efficacy and toxicity Chemotherapy (chemo) cyclical treatment is widely used in many cancer types in order to eradicate primary cancer cells and metastasis. Often, more than a single chemotherapeutic agent with or without surgical intervention and / or radiation is more effective and might improve survival benefit compared to a monotherapy approach1, 2. More than 100 different types of chemo drugs are available for cancer treatment and can be divided according to the pharmacological activities. For example, "alkylating-like" agents such as platinum-based drugs and cell cycle nonspecific anthracyclines directly damage the DNA inside the cancer cells and prevent cancer cells from dividing. Nucleoside analogues, such as Gemcitabine, 5FU and fludarabine, replacing the natural building blocks of DNA and RNA and interfere with the cell metabolism and nucleic acids synthesis. Topoisomerase inhibitors such as irinotecan, topotecan and SN-38 (the active metabolite of Irinotecan), are extracted from natural sources. Others such as Taxanes are isolated from plants (also known as plants alkaloids) and some isolated from a soildwelling fungus such as Streptomyces (daunorubicin and doxorubicin). Administering bolus doses of cytotoxic chemo drugs cause damage not only to cancer cells but also to healthy tissues. The effectiveness of the treatment is affected by a delicate balance between the ability to selectively kill the cancer cells without damaging healthy cells. Due to systemic, non-selective distribution, chemo treatment usually is much less effective to cancer cells since the therapeutic level reaching its target cells is low and thus it may cause only to a marginal improvement in patients overall survival rates. Other issues such as liver, lung, kidneys and immune toxicity and tumor drug resistance are major factors that need special attention in order to improve patient’s survival rate and quality of life. Therefore, more effective cancer therapies are needed both in terms of new classes of cytotoxic drugs and in terms of developing focused drug delivery vehicles to minimize the adverse effects and maximize the therapeutic effect, thus enhance the survival of patients with metastatic or advanced stage cancer disease.

Nanocarriers (NCs) as anti-cancer drug delivery platforms Collectively, nanomedicines offer a wide array of solutions based on diverse types of NCs in order to enhance the therapeutic benefit of chemo treatments by exploiting the tolerated doses that can be administrated to patients and simultaneously reduce


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the substantial adverse effects often seen with free chemo3-8. In addition, NCs offer the possibility to deliver novel biologicals such as therapeutic nucleic acids, peptides and proteins in order to explore novel strategies for effectively eradicating cancer cells. Current molecular and cellular medicines offer the potential to distinguish between healthy and cancer cells by means of identification of surface proteins that are predominantly expressed on cancer cells versus on healthy cells9-12, or by means of unique molecular signatures that are highly specific to cancer cells using “omics” strategies such as genomics, transcriptomics, proteomic and metabolomic analysis4, 13, 14

. In addition, it offers the ability to deliver more payloads per recognition site, e.g.

~ 10,000 doxorubicin molecules can be encapsulated in one liposome15, 16 and 4,000 siRNA molecules per lipid-based nanoparticle17. These NCs can protect the drug payload from the body hostile environment until it is released into the tumor microenvironment (TME) using either a burst release18, 19 or controlled sustained drug release depot in order to achieve prolonged therapeutic action18, 20-22. When and if this ‘drug release delay mechanism' functions, the NC is supposed to release its cytotoxic ammunition content within the TME over an extensive period of time improves patient's quality of life by decreasing the frequent drug dosing and potentially increasing the therapeutic window. NCs such as liposomes, polymeric nanoparticles (NPs), inorganic NPs, soluble polymers dendrimers and polymeric micelles23, 24 have gained much attention according to their attractive biological properties such as biocompatibility, biodegradability and the ability to overcome poor aqueous solubility of certain chemo by entrapment of both hydrophilic and hydrophobic drugs. For example, paclitaxel which exhibits poor solubility in water is delivered with adjuvants to increase its bioavailability (e.g. Taxol®). However, the castor oil-based adjuvant (Cremophor EL) caused toxic events, and can trigger severe side effects including hypersensitivity, neurotoxicity and neuropathy25, 26, which eventually may cause to treatment failure. To reduce the toxicity of Cremophor EL and to improve the overall efficacy of Paclitaxel, an albumin bound formulation (Abraxane®) was developed. Although Abraxane® and Taxol® are both effective chemo drugs for the treatment of advanced solid tumors, Abraxane® significantly improves the safety and overall response rate over Taxol but without significant improvement in overall survival rate27. NCs may have a huge impact on patient compliance mostly by reducing toxicity and frequency of dosing. However, it seems that the nanomedicine modality is far from reaching its full potential, at least according to the enormous "valley of death" gap



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between the numbers of NCs, which are currently under clinical evaluation compared with the number of FDA approved NCs as anti-cancer drugs. From 1995 - when the first liposomal chemo drug has been clinically approved by the FDA (Doxil™ in 1995, DaunoXome™ in 1996,) up today, only few liposomal based anti-cancer drugs formulations were approved by the FDA (Table 1). Currently, vast numbers of nano-scale liposomal based drugs formulations are under different stages of preclinical and clinical trials but only small numbers of new drugs are approved28. Most likely due to lack of efficiency and/ or toxicity issues and hurdles in Chemistry, Manufacturing and Control (CMC), which is the most challenging part when translating NCs based drugs into the clinic. The bridging above the valley of death is the key to a successful nanomedicine based drug delivery system. More FDA approved NCs for anti-cancer drugs, which will demonstrate a significant therapeutic benefit without introducing new types of adverse effects are in need. Table 1: Examples of FDA approved liposomal-based anti-cancer drugs

Compound

Commercial name

Liposomes Daunorubicin Doxorubicin (PEGliposomes)

Indications

Status

DaunoXome™ Kaposi’s sarcoma Doxil ™/ Caelyx™ Refractory Kaposi’s sarcoma; recurrent breast cancer; ovarian cancer

Market Market

Doxorubicin (Non PEGylated liposomes)

Myocet™

Combinational therapy of recurrent breast cancer

Market

liposomal vincristine sulphate Cytarabine liposome

Marqibo™

Market

Liposomal Cisplatinum

Lipoplatin™

lymphoblastic leukemia Esophageal Cancer Lymphomatous meningitis Non-squamous NSCLC mainly composed of adenocarcinomas Pancreatic cancer

DepoCyt™

Market

Market

Below we discuss some potential reasons why NCs as anti-cancer drugs do not realize their full potential. 1. Matching the NCs delivery mode of action (MoA) to the tumor type


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Intracellular delivery of drugs via NCs remains challenging. It is essential to understand the particular tumor biology and match the best NC available however, this is not a trivial task. The diversity in tumors in general and the heterogeneity of cells in a particular tumor will add complexity to the already complex design of NCs. Systemic administration of NCs could affect the encapsulated drug and its effectiveness (e.g. an immature efflux of the therapeutic payload from the NCs means that the NCs will most likely reach the tumor site as a drug-free NC). In addition, several considerations must be taken into account when NCs are administrated systemically (Figure 1). They will undergo dilution in the bloodstream. NCs’ pharmacokinetics and biodistribution will be determined based on several factors: the absorption, distribution, metabolism and their excretion (ADME), the materials by which they are made off; their surface charge and their curvature that can be easily tagged by proteins (mostly from the complement family) in order to alert the immune system29-32. Moreover, how these NCs penetrate tumors, and by which MoA they release their payload is an additional factor that can determine the effectiveness of the treatment and relates to the tumor biology33. NCs MoA can be divided into passive tissue targeting or active cellular targeting strategies3. The passive tissue targeting MoA relays on the ‘leaky’ nature of blood vessels next to the tumor and the ineffective lymphatic drainage known as the Enhanced Permeability and Retention (EPR) effect, which permits selective penetration of NCs into the tumor vicinity. It is crucial to choose the appropriate delivery strategy and match it to the specific tumor since passive tissue delivery may be ineffective in cases of poor vascularization and may evolve in treatment failure. For example, prostate and pancreatic tumors as well as metastatic liver cancer, are poorly vascularized and thus tumor penetration via EPR effect is likely to be ineffective34, 35. However, even in highly vascularized tumors, the type of the tumor and origin is not enough to rely solely on EPR effect since in many cases the released drug will not reach the inner tumor layers where cancer stem cells (CSC) or tumor initiating cells are often reside (necrotic inner core or deeper embedded CSC niches)36.



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Figure 1: Bridging the valley of death between developing nanomedicines at the lab scale to clinical translation. In order to increase the chances to effectively translate lab scale drugs in the form of NCs into new clinical modalities, researchers should consider to use active cellular targeting strategies (instead of passive tissue targeting approaches); Loading several drugs into a single NC (instead a single agent) in order to increase the potential effectiveness of the therapeutic outcome; Use the most suitable animal model for the indicated disease (instead of xenografted mice); Improve the analytical measurements and stability testing of NCs loaded with drugs in the blood/plasma (instead of in saline solution); Considering to integrate scalable manufacturing equipment in the early R&D steps (instead of small scale equipment) to streamline the NCs development process.

The NCs treatment modality should fit to the tumor vascular phenotype. Developing new methods in order to enhance tumor vascular permeability will attribute to efficient penetration of the NCs into the TME and enhancement of treatment effectiveness. Currently, some efforts are being made to develop strategies to probe the EPR in a particular patient via imaging modalities such as MRI or PET/CT. These strategies are based on pre-injecting patients with iron oxide NPs (in the case of MRI) or by injecting size define nanoliposomes with

64

Cu (in the case of PET/CT) in order to

quantify the EPR dimensions and better fit patients with the appropriate NC modality 37

.

NCs surface functionalized with active cellular targeting strategies such as natural ligands, peptides, antibodies and nucleic acids on their surface allow high affinity interactions with abundant tumor cells surface receptors hence increasing binding and cellular uptake into the tumor cells and reducing off target effects or effecting


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bystander cells3, 38. Together with its inimitable challenging targeting delivery properties as reaching disperse tumor cells as in hematological malignancies39 and its higher loaded drug cellular uptake, targeted NCs still need to be modified in order to have a better biodistribution profile and an improved tumor localization effect compared to non-targeted delivery systems40.

2. The key to a ‘long-term’ clinical success is based on drug combination NCs In order to control the complexity underlying cancer biology driven by the tumor cellular and immune cells interactions, modulating immune response is one of many parameters must be taken into account when a new formulation based on NCs is designed as a cancer therapy candidate. The ability to entrap multiple drugs in a single NC offers potentially more effective therapeutic outcome than a single drug entrapped in a NC. This strategy of combinational therapy within a single NC is based on the physicochemical and structural characteristics of the NC: The advantage of loading for example, different hydrophilic drugs in the inner aqueous compartments of a drug carrier in one hand and using surfactant self-assembly properties in order to conjugate also hydrophobic drugs on the other hand1 may provide a scaffold for testing different combinational therapies in the clinic. Each drug acts on a particular pathway in order to inhibit tumor growth, enables only a short term and limited therapeutic effect. While different drugs that act on several pathways simultaneously, could potentially improve the therapeutic outcome, for example, by bypassing drug resistance, changing the balance between drug influx to drug efflux that ultimately may cause a long-term therapeutic benefit to patients. Additionally, the use of mixed surfactants (such as anionic, cationic and non-ionic mixed surfactant micelles) are more effective wetting anti-microbial agents than a single surfactant and can act also as an efficient apoptotic agents in cancer cells41, 42. Smarter drugs within NCs are these, which are coated with tumor-targeting molecules on its surface that enable high specificity with lower toxicity in order to decrease

bystander

effect

on

healthy

cells.

These

strategies

combine

immunotherapy together with the conventional chemotherapy (or biological drugs such as small interfering RNAs; siRNAs) for eradicating tumors; could provide a synergistic therapeutic effect43. Examples for immunotherapy combinations are selective inhibition of tumor infiltrated immune cells, elimination of tumor suppressive genes (by a specific gene knockdown) and activation of the immune response against cancer cells.



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The vast combinations, different dosages, dosing regiments for testing efficacy, solubility differences, loading efficiency, control drug release, and toxicity effects of the combined drugs loaded in the same NCs are considered a big hurdle, in order to find the optimal conditions versus potent drugs combination, which holds promising therapeutic effect. Using Fourier Transform Infrared (FTIR) spectral analysis for testing drug solubility, different active methods of drug loading, imaging techniques such as Forster resonance energy transfer (FRET) to test the stability44 may overcome some of these hurdles. In order to overcome some potential adverse effects, while selecting the drug combination, researchers should select drugs, which work under different MoA. These drugs may meet this criterion45. The combination number of experimental parameters makes this drug optimization process a very long-, complex-, highly researcher professionalism- depend, and suffers from lack of robustness in the production of NCs. Hence, it is a major challenge to optimize the experimental biological design approach including ‘old’ drugs entrapped within NCs developmental attitude in order to increase the treatment effectiveness: Move from a temporary tumor growth inhibition to an advanced long-term disease handling is the task of the researchers that are working in the field of nanomedicine. In order to predict in vivo anti-tumor behavior of combined drugs, experimental methods, such as in vitro high throughput screening, integrated with quantitative automated mathematical models should be employed. For example, combines stochastic algorithm based approaches such as the closed-loop optimization method, which is based on a phenotypic response rather than using popular biological experiments with a single outcome relays on a single pathway genotype46. This can contribute significantly to more effective combination drugs search in a significantly shorter time. In addition, to preclinical use, this method can also be helpful with the selection of the most suitable personalized drugs loaded within NCs for effective cancer therapy. In order to learn more about the biodistribution of the different combinational therapies, conjugating different imaging molecules (such as fluorescent different dyes or radioactive isotopes) together with non-invasive in vivo imaging tracking technologies such as IVIS, PET/CT, SPECT/CT, and PET/MRI should be included in the preclinical phase and as early as possible47.

3. Non-predictive animal models


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Animal studies are essential preclinical models and a basic tool in the drug development field in order to understand the efficacy and feasibility of a new drug. Thus, a detailed discussion of the quality of the animal models as predictive tools for anti-cancer drug development and for measuring the performance of NCs that are systemically administrated in a whole animal setting is crucial. However, developing of animal models, which provide reliable prediction for the human cancers, is hampered by the lack of understanding of the complexity of cancer. Most of the preclinical cancer research is performed in immune deficient animals, such as xenograft models, which are based on Nude/ SCID or Rag mice that suffer from low correlation with the human clinical disease and without an intact immune system it is hard to predict potential adverse effects such as immune suppression or activation 30, 48

.

One option for replacing these models with a more reliable human surrogate cancer model is the use of tumor bearing mice having also a humanized immune system. However, these are highly sensitive mice and the engraftment of many types of human tumors is therefore limited. In addition, many human cell lines, which are commonly used as popular cells for inoculation of human tumors in vivo poorly resemble the biological tumor and lack a real tumor microenvironment. For example, 60% of PubMed publications on ovarian cancer cell lines are focus on SKOV3 and A2780, both cell lines are poorly suited as proper tissue subtype model for ovarian cancer49. The ability to translate information accepted from such in vivo false human cancer models into clinical setting is problematic since these models are not mimicking the 'real' biological environment in the human body. It is likely to be one of the reasons for NCs failure in advanced clinical trials. Around 90% of new anticancer drugs that had shown a significant antitumor efficacy in murine studies will fail in clinical trials50. Scientists should evaluate and select the most similar tumor genomic profile cell line/ animal model for their in vitro/in vivo set of experiments in order to have predictive data that could be translate later into the clinic. The necessity for an improve 'clinical predictive' animal cancer model, representing each cancer subtype is crucial in order to elevate success rate in advanced clinical phases and streamline the process of drug development for NCs. An alternative approach for refining predictive animal model must be considered such as orthotopic models that mimic the tumor site. An additional example is a transgenic mouse model based on humanized mice, which allows enhancement of the human immune system with reduced mouse innate immune responses51. However, there is



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also some limitation to such models. For example, limited peripheral lymph nodes development exists in the immune-deficient IL2 receptor γ chain knockout (IL2Rgnull, Rag) mice or expression of HLA class II alleles, which basically reduce the potential immune response of the tumor engrafted mice to the NCs. Efforts should be made to develop better human immunity animal models as a translational tool between animal model and human tumor immunology. In addition to the extent rodent's cancer models, investigators need to find a better human disease model as well as pharmacokinetics and pharmacodynamics of NCs drug behavior predictors. Another alternative is to implant patient's derived tumor cells in mice. This may mimic partially the human tumor microenvironment in a personalized medicine manner; however it does not reflect reliably the human immune system52.

The use of larger animals such as rabbits, dogs, pigs or non-human primates having a particular tumor (either developed spontaneously or engrafted into unique animals) should be considered and use more frequently. Pigs, for example share higher sequence homology with human and represent a better and more suitable animal model in a comparison to rodents. However, even in the cause of pigs there might be some concerns since it was recently found that pigs have sensitive complement system and could induce complement activation when different types of NCs are being injected such as liposomes53,

54

. Different limitations as budget and animal

housing may minimize the use of these larger animals. However the ability to contract out some of these essential experiments may be beneficial in developing improved NCs.

4. The lack of reliable techniques related to measurements of NCs stability in human fluids Increasing the therapeutic effect using NCs platforms depends largely on the stability of these NCs and prolonging the half-life of the carriers in the human bloodstream. Choosing suitable NCs composition, not only its use as a drug shelter, is a critical step in the way to a successful clinical translation. Interactions with the biological environment such as body fluids composition, immune cells, complement fragments, proteins and blood vessels structure influence the NCs’ clearance rate, carrier structure, drug dissociation profile and may attribute to destabilization of the NCs leading to early, non-controllable release of the encapsulated drug, which decrease specificity and efficiency. Attempt to prolong the


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half-life circulation time by increasing the NCs’ plasma stability is demonstrated by the wide use of polyethylene glycol (PEG), which is mainly characterized by increasing the circulation time and improve the evasion by the immune systems. Some FDA approved examples of clinically PEG composed liposomes are Lipoplatin™, Mitoxantrone (Novantrone®) and Doxil®. However, various examples are documented for drugs entrapped within NCs, which were expected to be stable in body fluids according to in vitro stability studies such as critical micelle concentrations (cmc), colloidal stability and drug release profile but exhibit poor drug retention in circulation, when the drug was quickly released (

Transforming Nanomedicines From Lab Scale Production to Novel

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